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Efficient discovery of multilevel spatial association rules using partitions

https://doi.org/10.1016/j.infsof.2004.03.007
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/3-540-60159-7_4openalex-snapshot
Discovery of spatial association rules in geographic information databases
inferredcites →https://doi.org/10.1016/s0169-023x(00)00017-3openalex-snapshot
Mining multiple-level spatial association rules for objects with a broad boundary
inferredcites →https://doi.org/10.1109/69.846291openalex-snapshot
Scalable algorithms for association mining
inferredcites →https://doi.org/10.1109/69.956106openalex-snapshot
A graph-based approach for discovering various types of association rules
inferredcites →https://doi.org/10.1109/icde.2000.839445openalex-snapshot
Mining recurrent items in multimedia with progressive resolution refinement
inferredcites →https://doi.org/10.1145/223784.223813openalex-snapshot
An effective hash-based algorithm for mining association rules
inferredcites →https://doi.org/10.5860/choice.49-3305openalex-snapshot
Data mining: concepts and techniques

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Nature-Inspired Approaches to Mining Trend Patterns in Spatial Databases
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AntTrend: Stigmergetic Discovery of Spatial Trends
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Maximal Sub-prevalent Co-location Patterns and Efficient Mining Algorithms
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AOG-ags Algorithms and Applications
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Privacy-Preserving Data Mining in Spatiotemporal Databases Based on Mining Negative Association Rules
inferred← citeshttps://doi.org/10.1007/978-981-16-7566-9_3openalex-snapshot
Maximal Sub-prevalent Co-location Patterns
inferred← citeshttps://doi.org/10.1007/978-981-16-7566-9_7openalex-snapshot
Dominant Spatial Co-location Patterns
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Spatially enabled emergency event analysis using a multi-level association rule mining method
inferred← citeshttps://doi.org/10.1007/s11069-013-0833-5openalex-snapshot
Hybrid spatial data mining methods for site selection of emergency response centers
inferred← citeshttps://doi.org/10.1007/s11280-018-0646-2openalex-snapshot
Mining maximal sub-prevalent co-location patterns
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Spatially enabled customer segmentation using a data classification method with uncertain predicates
inferred← citeshttps://doi.org/10.1016/j.eswa.2008.02.056openalex-snapshot
A hybrid spatial data clustering method for site selection: The data driven approach of GIS mining
inferred← citeshttps://doi.org/10.1016/j.ins.2009.05.023openalex-snapshot
An order-clique-based approach for mining maximal co-locations
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Spatial Data Mining for Optimized Selection of Facility Locations in Field-based Services
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A new join-less approach for co-location pattern mining
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Emergency Resource Planning by Using Spatial Data Association Rule Mining and Linear Programming Method
inferred← citeshttps://doi.org/10.1109/fskd.2015.7382013openalex-snapshot
Incremental mining of co-locations from spatial database
inferred← citeshttps://doi.org/10.1109/geoinformatics.2011.5980870openalex-snapshot
Extracting spatial association rules from the maximum frequent itemsets based on Boolean matrix
inferred← citeshttps://doi.org/10.1109/icacte.2008.163openalex-snapshot
Discovering Multiple-Level Association Rules from Transactional Databases with Consideration of Temporal Characteristics of Products' Discounts Rates
inferred← citeshttps://doi.org/10.1109/iccitechn.2008.4803105openalex-snapshot
A Data mining approach for finding optimal discount of retail assortments
inferred← citeshttps://doi.org/10.1109/icmss.2010.5577834openalex-snapshot
Discovery of Multi-Level Spatial Association Rules Based on DE-9IM
inferred← citeshttps://doi.org/10.1109/tkde.2011.256openalex-snapshot
Finding Probabilistic Prevalent Colocations in Spatially Uncertain Data Sets
inferred← citeshttps://doi.org/10.1109/wicom.2008.2628openalex-snapshot
Association Rule Mining on Spatio-Temporal Processes
inferred← citeshttps://doi.org/10.17762/msea.v71i3s.19openalex-snapshot
Maximum Co-Location Patterns of Mining Based on Count-Ordered Citations-Analysis of Spatial Databases
inferred← citeshttps://doi.org/10.18178/ijmlc.2022.12.1.1074openalex-snapshot
Mining Maximal Co-location Patterns Based on the Count-Ordered Instances-Tree in Spatial Databases
inferred← citeshttps://doi.org/10.3233/ida-2009-0356openalex-snapshot
Effective spatial clustering methods for optimal facility establishment
inferred← citeshttps://doi.org/10.4236/jdaip.2013.14010openalex-snapshot
Spatial Multidimensional Association Rules Mining in Forest Fire Data
inferred← citeshttps://doi.org/10.47893/ijcsi.2012.1032openalex-snapshot
Selection of Optimal Discount of Retail Assortments with Data Mining Approach
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